Accurate, Fully-Automated NMR Spectral Profiling for Metabolomics DOI Creative Commons

Siamak Ravanbakhsh,

Philip L.‐F. Liu,

Trent C. Bjordahl

et al.

PLoS ONE, Journal Year: 2015, Volume and Issue: 10(5), P. e0124219 - e0124219

Published: May 27, 2015

Many diseases cause significant changes to the concentrations of small molecules (aka metabolites) that appear in a person's biofluids, which means such can often be readily detected from "metabolic profile". This information extracted biofluid's NMR spectrum. Today, this is done manually by trained human experts, process relatively slow, expensive and error-prone. paper presents tool, Bayesil, quickly, accurately autonomously produce complex (e.g., serum or CSF) metabolic profile 1D1H requires first performing several spectral processing steps then matching resulting spectrum against reference compound library, contains "signatures" each relevant metabolite. these are novel algorithms our step views as an inference problem within probabilistic graphical model rapidly approximates most probable profile. Our extensive studies on diverse set mixtures, show Bayesil find concentration all NMR-detectable metabolites (~90% correct identification ~10% quantification error), <5minutes single CPU. These results demonstrate fully-automatic publicly-accessible system provides quantitative profiling effectively -- with accuracy meets exceeds performance experts. We anticipate tool will usher high-throughput metabolomics enable wealth new applications clinical settings. Available at http://www.bayesil.ca.

Language: Английский

A guide to the identification of metabolites in NMR-based metabonomics/metabolomics experiments DOI Creative Commons
Anthony C. Dona,

Michael Kyriakides,

Flora Scott

et al.

Computational and Structural Biotechnology Journal, Journal Year: 2016, Volume and Issue: 14, P. 135 - 153

Published: Jan. 1, 2016

Metabonomics/metabolomics is an important science for the understanding of biological systems and prediction their behaviour, through profiling metabolites. Two technologies are routinely used in order to analyse metabolite profiles fluids: nuclear magnetic resonance (NMR) spectroscopy mass spectrometry (MS), latter typically with hyphenation a chromatography system such as liquid (LC), configuration known LC-MS. With both NMR MS-based detection technologies, identification metabolites sample remains significant obstacle bottleneck. This article provides guidance on methods fluids using spectroscopy, illustrated examples from recent studies mice.

Language: Английский

Citations

290
Molecular Probes, Chemosensors, and Nanosensors for Optical Detection of Biorelevant Molecules and Ions in Aqueous Media and Biofluids DOI Creative Commons
Joana Krämer, Rui Kang, Laura Grimm

et al.

Chemical Reviews, Journal Year: 2022, Volume and Issue: 122(3), P. 3459 - 3636

Published: Jan. 7, 2022

Synthetic molecular probes, chemosensors, and nanosensors used in combination with innovative assay protocols hold great potential for the development of robust, low-cost, fast-responding sensors that are applicable biofluids (urine, blood, saliva). Particularly, metabolites, neurotransmitters, drugs, inorganic ions is highly desirable due to a lack suitable biosensors. In addition, monitoring analysis metabolic signaling networks cells organisms by optical probes chemosensors becoming increasingly important biology medicine. Thus, new perspectives personalized diagnostics, theranostics, biochemical/medical research will be unlocked when standing limitations artificial binders receptors overcome. this review, we survey synthetic sensing systems have promising (future) application detection small molecules, cations, anions aqueous media biofluids. Special attention was given provide readily measurable signal through dynamic covalent chemistry, supramolecular host-guest interactions, or nanoparticles featuring plasmonic effects. This review shall also enable reader evaluate current performance terms sensitivity selectivity respect practical requirement, thereby inspiring ideas further advanced systems.

Language: Английский

Citations

286
Recent advances in the application of metabolomics for food safety control and food quality analyses DOI
Shubo Li, Yufeng Tian,

Pingyingzi Jiang

et al.

Critical Reviews in Food Science and Nutrition, Journal Year: 2020, Volume and Issue: 61(9), P. 1448 - 1469

Published: May 22, 2020

As one of the omics fields, metabolomics has unique advantages in facilitating understanding physiological and pathological activities biology, physiology, pathology, food science. In this review, based on developments analytical chemistry tools, cheminformatics, bioinformatics methods, we highlight current applications safety, authenticity quality, traceability. Additionally, combined use with other techniques for "foodomics" is comprehensively described. Finally, latest advances, practical challenges limitations, requirements related to application are critically discussed, providing new insight into analysis.

Language: Английский

Citations

284
Mass spectrometric based approaches in urine metabolomics and biomarker discovery DOI Open Access

Mona M. Khamis,

Darryl J. Adamko, Anas El‐Aneed

et al.

Mass Spectrometry Reviews, Journal Year: 2015, Volume and Issue: 36(2), P. 115 - 134

Published: April 16, 2015

Urine metabolomics has recently emerged as a prominent field for the discovery of non‐invasive biomarkers that can detect subtle metabolic discrepancies in response to specific disease or therapeutic intervention. Urine, compared other biofluids, is characterized by its ease collection, richness metabolites and ability reflect imbalances all biochemical pathways within body. Following urine collection metabolomic analysis, samples must be immediately frozen quench any biogenic and/or non‐biogenic chemical reactions. According aim experiment; sample preparation vary from simple procedures such filtration more extraction protocols liquid‐liquid extraction. Due lack comprehensive studies on metabolome stability, higher storage temperatures (i.e. 4°C) repetitive freeze‐thaw cycles should avoided. To date, among analytical techniques, mass spectrometry (MS) provides best sensitivity, selectivity identification capabilities analyze majority metabolite composition urine. Combined with qualitative quantitative MS, due continuous improvements related technologies ultra high‐performance liquid chromatography [UPLC] hydrophilic interaction [HILIC]), (LC)‐MS unequivocally most utilized informative tool employed metabolomics. Furthermore, differential isotope tagging techniques provided solution ion suppression matrix thus allowing analysis. In addition LC‐MS, MS‐based have been These include direct injection (infusion)‐MS, capillary electrophoresis‐MS gas chromatography‐MS. this article, current progresses different exploring well recent findings providing potentially diagnostic urinary are discussed. © 2015 Wiley Periodicals, Inc. Mass Spec Rev 36:115–134, 2017.

Language: Английский

Citations

280
Accurate, Fully-Automated NMR Spectral Profiling for Metabolomics DOI Creative Commons

Siamak Ravanbakhsh,

Philip L.‐F. Liu,

Trent C. Bjordahl

et al.

PLoS ONE, Journal Year: 2015, Volume and Issue: 10(5), P. e0124219 - e0124219

Published: May 27, 2015

Many diseases cause significant changes to the concentrations of small molecules (aka metabolites) that appear in a person's biofluids, which means such can often be readily detected from "metabolic profile". This information extracted biofluid's NMR spectrum. Today, this is done manually by trained human experts, process relatively slow, expensive and error-prone. paper presents tool, Bayesil, quickly, accurately autonomously produce complex (e.g., serum or CSF) metabolic profile 1D1H requires first performing several spectral processing steps then matching resulting spectrum against reference compound library, contains "signatures" each relevant metabolite. these are novel algorithms our step views as an inference problem within probabilistic graphical model rapidly approximates most probable profile. Our extensive studies on diverse set mixtures, show Bayesil find concentration all NMR-detectable metabolites (~90% correct identification ~10% quantification error), <5minutes single CPU. These results demonstrate fully-automatic publicly-accessible system provides quantitative profiling effectively -- with accuracy meets exceeds performance experts. We anticipate tool will usher high-throughput metabolomics enable wealth new applications clinical settings. Available at http://www.bayesil.ca.

Language: Английский

Citations

279